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Record W7160369547

Book Review: Stephen Kantrowitz, Citizens of a Stolen Land: A Ho-Chunk History of the Nineteenth-Century United States.

2024· article· en· W7160369547 on OpenAlexaboutno aff
Grant Arndt

Bibliographic record

VenueIowa State University Digital Repository (Iowa State University) · 2024
Typearticle
Languageen
FieldArts and Humanities
TopicDiverse Historical and Scientific Studies
Canadian institutionsnot available
Fundersnot available
KeywordsHomelandReservationEPICGeorge (robot)Face (sociological concept)Quarter (Canadian coin)
DOInot available

Abstract

fetched live from OpenAlex

Stephen Kantrowitz’s important and illuminating Citizens of a Stolen Land tells of the Ho-Chunk people’s epic and ultimately successful struggle to retain a place in their midwestern homeland in the face of half of a century of settler invasion, coerced treaties, forced marches, suffering, and death, all carried out by the United States in the name of “civilization.” Although it was only a marginal part of the Ho-Chunk homeland in Wisconsin, following an 1837 treaty, Iowa became the destination of the first military removal of Ho-Chunk people from their homes. They were relocated to a reservation established on the “Neutral Grounds” between treaty-recognized territories of the Dakota and Sauk Nations. In 1848, this Iowa reservation became the first from which they were forced to move, a pattern repeated with a series of reservations in Minnesota, then South Dakota, and finally Nebraska.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.046
Threshold uncertainty score0.155

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.005
Science and technology studies0.0010.002
Scholarly communication0.0040.005
Open science0.0020.002
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0460.039

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.011
GPT teacher head0.154
Teacher spread0.143 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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